Research and Design of Context UX Data Analysis System
At present, user researchers have problems in UX (User experience) data analysis, such as low efficiency, inaccurate context data identification, and low satisfaction of analysis process. Therefore, in order to solve these problems, this paper proposes a
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Abstract. At present, user researchers have problems in UX (User experience) data analysis, such as low efficiency, inaccurate context data identification, and low satisfaction of analysis process. Therefore, in order to solve these problems, this paper proposes a design context UX data analysis system to compensate for the shortcomings in the data analysis process. This paper takes the analysis of UX data collected by the CAUX (Context-Aware User Experience) tool as an example, using the relevant methods in Cognitive Task Analysis (CTA), and on the basis of sensemaking loop model, explore the data analysis process of UX researchers through experiments. And carry out demand research for each stage of the analysis process, design a context UX data analysis system according to the requirements. This thesis summarizes the model of UX data analysis process, completes the design of context UX data analysis system, and evaluation experiment proves that the system can effectively solve the problems in the UX data analysis process, and provides a new idea for the UX research practice in the mobile Internet environment. Keywords: Context aware
Cognitive task analysis Data analysis
1 Introduction With the rapid development of mobile Internet, user experience has become an important factor in determining the success or failure of information technology products. Therefore, in order to improve the user experience, user researchers will collect various “data” through data collection tools to analyze user behavior. The collected UX data will be analyzed by data analysis tools. Currently, common data analysis tools are mostly independent third-party analysis tools. PA Nogueira [1] designed and developed an analysis tool for digital game UX data to ensure that user researchers can perform objective data analysis without disturbing the game player experience; Miller A [2] established automatic data analysis and visualization tool evaluation standards; S Garg [3] developed a visual analysis tool based on machine learning and deductive reasoning techniques to help users easily analyze relationships between complex data sets. However, these tools still have many shortcomings in the actual case study. For example, UX researchers need to manually sort and filter data in the data analysis process, and the data that is closely coupled with the context cannot be effectively analyzed and presented, lead to low efficiency and low satisfaction in the
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Q. Liu et al. (Eds.): CENet 2020, AISC 1274, pp. 661–669, 2021. https://doi.org/10.1007/978-981-15-8462-6_75
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X. Fu and Z. Liu
data analysis process. Therefore, this paper proposes a design context UX data analysis system to compensate for the shortcomings in the data analysis process. In order to solve these problems, we need to understand the process of researchers analyzing UX data. This paper uses the CTA method to understand this process. CTA uses a variety of inter
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